{"id":"W2315018354","doi":"10.1142/9781860948732_0030","title":"UNCOVERING THE STRUCTURAL BASIS OF PROTEIN INTERACTIONS WITH EFFICIENT CLUSTERING OF 3-D INTERACTION INTERFACES","year":2007,"lang":"en","type":"article","venue":"Computational Systems Bioinformatics","topic":"Protein Structure and Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; University of Toronto; Mount Sinai Hospital","funders":"","keywords":"Computer science; Cluster analysis; Basis (linear algebra); Protein–protein interaction; Human–computer interaction; Data mining; Artificial intelligence; Chemistry; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001938188,0.0001009101,0.000122044,0.00006198667,0.00006363454,0.0000211095,0.0001264933,0.00004142392,0.000001860216],"category_scores_gemma":[0.00002780156,0.00006619511,0.00004088911,0.0001074797,0.00007536692,0.00001213868,0.00007466137,0.00007292537,6.922253e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002637092,"about_ca_system_score_gemma":0.00004066352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004420891,"about_ca_topic_score_gemma":0.00003983682,"domain_scores_codex":[0.9991641,0.0000182767,0.0004528847,0.00007640864,0.0001839084,0.0001044203],"domain_scores_gemma":[0.9991979,0.00003875432,0.0003965609,0.0001427845,0.0001995188,0.0000244645],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001478764,0.00001029333,0.0004864322,0.0002296861,0.00008350196,2.485322e-7,0.0004904793,0.9815305,0.01393316,0.000360703,0.000008379649,0.002718769],"study_design_scores_gemma":[0.000558951,0.0003631277,0.003980962,0.0003837749,0.00002911964,0.0001572721,0.002946909,0.9209431,0.06990033,0.0001178223,0.0004023062,0.0002163265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.605655,0.00004720928,0.3935755,0.000008354979,0.0001418564,0.0002199693,0.00001393105,0.00000440991,0.0003337711],"genre_scores_gemma":[0.98927,8.421885e-7,0.01058672,0.000009876841,0.00004903319,0.000006304063,0.00004765958,0.000007129449,0.00002238576],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.383615,"threshold_uncertainty_score":0.2699358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007201058886584483,"score_gpt":0.2486894658346331,"score_spread":0.2414884069480486,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}